It’s all anyone can seem to talk about these days, but what really could Artificial Intelligence (AI) become? We look at this new transformative technology and discusses the economic ramifications of a post-AI world. And, importantly, its impact on sustainability.
AI already forms a major part of our lives. The use of natural language processors like iPhone’s Siri to the song recommendations we receive in Spotify are just a few examples of its long-standing presence. But what actually is generative AI? Who better to explain than ChatGPT itself:
“Generative AI refers to a class of artificial intelligence models that create new content, such as text, images, or music, based on patterns and examples from a given dataset. These models employ techniques like deep learning and neural networks (which mimic the human brain) to generate original content that closely resembles the input data. By learning from large amounts of data, generative AI can produce realistic and creative outputs, making it useful in various applications like art, design, and content creation.”1
The success of ChatGPT has accelerated investment into both traditional and generative AI applications. This has boosted the demand for semiconductor chips produced by Nvidia, which are used to power the training of AI’s large underlying datasets, sending shares up 190% over the first half of 2023. Nvidia cannot ramp supply fast enough to keep up with the surge in demand for its AI solutions. So, is this the start of a generational shift in computing technology? Or will AI follow the disappointing path of other recently hyped technologies such as the metaverse and blockchain? Arguably, AI is different in that it offers tangible benefits for the real economy. With most of the world facing structural inflationary challenges linked to a shrinking labour force and deglobalisation, governments and enterprises alike are looking to invest in automation that can promote worker productivity. AI now has the potential to automate a number of business functions such as administration workflows, customer marketing and sales; a recent report by Accenture claims that generative AI could add $2.6-$4.4 trillion to the global economy per annum by supporting accelerated innovation and productivity (Figure 1).2
Figure 1: percentage move of Big Tech and the rest of the S&P 500
Source: McKinsey Report, June 2023
Microsoft is in the process of testing a number of “AI co-pilots” for its office applications supported by its investment in OpenAI. It recently launched an AI copilot for its software development platform GitHub, which can help make software developers up to 50% more efficient by automating coding. Intuit, is using generative AI in its MailChimp direct marketing software to enable small business customers to automatically draft emails to target customers.
As generative AI develops and matures, it can also play a greater role in innovation. AI can be used to advance “smart farming” techniques, enabling farmers to have higher yields while using fewer inputs. Around 50% of a farmer’s costs are from labour and fertilisers/pesticides but by using Deere’s smart solutions, farmers can save up to two thirds on herbicide and fertiliser usage, bringing clear environmental benefits.In time, Deere expects its solutions to reduce farmers’ input costs by 15%-25% while enabling a shift to full autonomous production systems by 2027. This brings social benefits in tackling high food inflation by lowering the cost of production.
There is also excitement around the use of AI in the healthcare sector. US healthcare spending has risen unsustainably to around 20% of GDP3, but studies have shown that 20%-30% of this spending is wasteful due largely to the administrative complexity of the system4. AI tools are being rolled out to doctors to both lower their administrative burden and increase the standard of care via doctor assistant tools. AI can also understand biology in a way humans cannot – this can accelerate the time-to-market for new innovative drugs.
We believe generative AI could be as revolutionary as the internet. It took 30 years for the internet to evolve- with some failures and stock corrections along the way – but ultimately it reshaped the world. As with all transitions, however, we need to ensure it is responsibly managed. This means, for example, using quality, proprietary datasets to retain high security and privacy standards. And although AI is most powerful when working in combination with humans, helping us to be smarter and more efficient, enterprises need to ensure retraining for those workers displaced by AI. Training AI models is also energy-intensive, so powering datacentres with renewable energy is vital.
Ultimately, sustainability and technology are intertwined. Key advances in technology, like AI, make us better equipped to tackle the planet’s growing environmental and social challenges.
